The curves certainly support the claim. With a Bachelor’s degree or higher (assuming the sample is random – unbiased), the chances are 98% that you will be employed. Conversely, without a high-school degree, the chances are only about 92% that you will be employed. (Looking at employment rates rather than unemployment rates puts a more positive spin on things :).) This chart shows a (perhaps) correct statement about the current state of affairs. However the inference that therefore we should be encouraging everyone to get BS-degrees so they will get employed (as proponed in the news clip) is flawed. It is flawed because it assumes that we live in a static environment where employers will continue to consider the bachelors degree as a strong employee credential.

Lets say we do manage to get everyone to graduate from a college. You can envision a world 10 years from now with these same curves, except the orange curve would be labeled “PhD degree or higher” (What could possibly be higher than a PhD degree?); the blue curve will be labeled “less than bachelor’s degree”; and, the remaining curves will be labeled with various degrees in between. One thing the chart does not address is whether the employment rate of BS-holders among the auto-mechanic industry is any higher than that of non-high-school graduates (I don’t know, I am just guessing no). Should we encourage the guy who loves to be a car-mechanic to get a bachelors? Realistically many people in jobs requiring a bachelors degree do not perform tasks that essentially rely on skills learned during their bachelors (to wit: that management consultant with a BA in art history).

What is happening here is that there are a finite number of jobs that require “academic skill”. There are more of these “academic” jobs than the mechanic-type of job which does not require academic education. Clearly employers hire the best people to do the job – they need a yardstick. And one popular yardstick is level of education. It is just a measuring tool that allows employers to rank-order candidates, and it is a valid metric (though, there is probably significant ethnic disparity in education levels and many would therefore use that as a justification that “this is a flawed metric and therefore should not be used in determining who to hire….” See my article: Metrics for Admission to Graduate School – GREs and all that.). By increasing the level of education of everyone, all we are doing is increasing the length of that yardstick. We still have that same number of “academic” jobs and they are still going to go to the top candidates as measured by the new yardstick – employers will adapt to the new yardstick. There will be one good side effect: the population will get more educated (perhaps). That is a good thing. On the flip side all the “mechanic”-type jobs will have to be filled with “academically” trained people, and to get an “academic” job you will need an MS or perhaps a PhD:

We will be wasting lots of resources training people with skills for jobs that do not need those skills – over-education. These resources include the additional time and money spent by the students and the resources spent by educators.

A plethora of convenient “online” for profit bachelors programs will erupt charging students for sub-par degrees, diluting the discriminative power of the BS. Therefore to differentiate themselves, the better students will have to get an MS or higher, yet another waste of time and resources by student and educator. Ultimately the effective cost of a useful education goes up.

We will not solve the jobs problem. There will still be the same number of “academic” jobs and the same number of “non-academic”-jobs. All our efforts will result in similar unemployment rates. The solution to getting more people employed is having more jobs, not having more BS’s. (We ignore the slight effect that more educated people might lead to more innovation which might create new jobs. This is because we are not talking about innovation here but about who gets to fill needed, existing positions.)

Game theoretically, it looks like we are headed in a bad direction: as an individual, the only hope is to get a higher and higher education to get a job. The spiral has already begun with online institutions even pretending to offer PhD degrees.

Beware the static reasoning trap: to reason and act on the basis that people or the environment will not adapt to your actions (the opposite of LeChatelier’s Principle).

Let’s educate everyone to at least the BS level: employers will adapt to ever-increasing levels of education without ever increasing real capabilities.

Let’s raise real-estate taxes (so we get more revenue to fund public programs): people adapt will move out. Such has happened to Troy, NY.

Let’s put a limit on deductions (such as charitable donations): people will donate less and the state will have to fund the shortfall in social services with the additional tax revenue.

Let’s impose a uniform 2 year TA limit on graduate students so that professors will have to fund every student for at least 3 years, generating considerable overhead income for the university: among other effects, professors might adapt and become conservative in admissions and only admit students when they have guaranteed funding in hand, thereby decreasing the size of the PhD program.

Let’s impose hard thresholds for standardized test scores and a laborious centralized process to get waivers to these thresholds, in this way ensuring rigorous uniform standards for incoming PhD students: professors might adapt and only consider applicants who pass those thresholds to avoid unnecessary hassles. Therefore, top candidates may be missed perhaps decreasing the over quality of the program.

Let’s increase the employer-mandated maternity leave from 6 weeks to 1 year (as it is in England), thereby further encouraging women to enter the workforce by making it more appealing: employers may adapt and be less likely to take on young women because they are factoring in the cost of a potential maternity leave; and this is hard if not impossible to police.

…and so on.

We cannot say whether the above actions are good or bad; but we can say that the reasoning to determine whether they are good or bad must incorporate the effects of how people or the environment will realistically adapt to new policies.